Does the Menu Task Predict Occupational Performance, Readmissions, and Falls After Stroke?
Bibliographic record
Abstract
Cognitive screening is crucial for all stroke clients since not identifying cognitive impairments can negatively affect health outcomes. The Montreal Cognitive Assessment (MoCA) is a commonly used neuropsychological screen in the acute setting. However, the Menu Task (MT), a standardized performance-based functional cognitive screen, may be better at identifying cognitive deficits in this population. This study aimed to determine (a) the correlation between the MT and the MoCA, and (b) which screen better predicts outcomes (occupational performance, falls, and readmissions) in stroke patients with mild cognitive deficits. Using a prospective predictive design, both screens were administered to 80 hospitalized adults upon admission. Thirty days postdischarge occupational performance, as per the modified Rankin Scale and the Lawton Instrumental Activities of Daily Living (IADL) scale, falls and readmissions data were collected. The results showed a small, nonsignificant positive correlation between the screens and the MT may be a better predictor of occupational performance and readmissions 1 month postdischarge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".